Automated Restaurant Bookings: Dirigì Group and Mister Pizza
DeepAgent's Voice AI answers on the first ring and confirms tables in seconds, 24/7. How many bookings are you losing while the phone rings?
If you manage a pizzeria or restaurant, you know this: during service, your hands are busy, and the phone rings. Automated restaurant bookings with Voice AI answer on the first ring, 24/7, eliminating missed calls and freeing up staff. This is what the Dirigì Group (Pizzeria Dirigì Jesolo and Mister Pizza) did with Alice, DeepAgent's AI voice assistant for restaurants. ## TL;DR - 24/7 Voice AI: immediate response, table confirmation, and zero missed calls during peak times. - 99.9% of inbound calls successfully completed in both locations. - 1,645 inbound calls handled in 25.2 total hours; average ~55–57 s. - Outbound: 35,825 calls for campaigns, 108 hours of conversation. - Over 38,000 total calls managed (inbound and outbound) during the period. ## Client Profile and Objectives The Dirigì Group manages two high-volume venues in Veneto: Pizzeria Dirigì in Jesolo (Via Andrea Bafile 232) and Mister Pizza. The objective: automate phone reservation management while maintaining the service style, courtesy, and speed typical of in-person dining, with an always-available voice AI for restaurants. ## The Challenge: Missed Calls During Service During peak times, staff have their hands full: serving tables, managing flows, and handling payments. The phone falls to a lower priority, with direct impacts on covers and revenue. - Calls dropped during peak hours. - Customers hanging up before a callback: lost bookings. - Distraction of front-of-house staff to answer the phone.  ## The Solution: Alice, DeepAgent's Voice Agent Alice answers every incoming call, collects essential data (date, time, covers, name, mobile, email), checks availability, and confirms immediately, with no manual intervention. ### Key Features - Handling special requests (e.g., gluten-free options for celiacs). - Escalation to a human operator for large groups or upon request. - Information about the venue: address, opening hours, job applications. - 24/7 coverage without increasing staff: AI voice assistant for restaurants integrated into the workflow. ### Booking Flow (Example) 1) Greeting and location verification. 2) Collection of date/time/covers. 3) Availability check. 4) Contact details and preferences (e.g., gluten-free). 5) Immediate confirmation with recap. 6) Optional human transfer for complex requests.  ## Rapid Implementation and Governance - Conversational script customized for menus, policies, and time slots. - Routing between locations and peak hours to reduce missed restaurant calls. - Centralized reporting: volumes, sentiment, outcomes, and average times. ## Results and KPIs (03/04–17/06/2026) - Pizzeria Dirigì Jesolo: **796** inbound, **795** successful (≈**99.9%**), **57 s** average, **~12.5 h** conversation. Sentiment: **129** positive, **538** neutral, **59** negative (~7%). - Mister Pizza: **849** inbound, **848** successful (≈**99.9%**), **54 s** average, **~12.7 h** conversation. - Outbound “PersonalG”: **35,825** calls, **~108 h** conversation. - Total: **over 38,000** calls managed overall. | Location/Type | Period | Inbound Handled | Successfully Completed | % Success | Average Duration | Conversation Hours | Sentiment (+/=/−) | Outbound | |---|---|---:|---:|---:|---:|---:|---|---:| | Pizzeria Dirigì (Jesolo) | 03/04–17/06/2026 | 796 | 795 | 99.9% | 57 s | ~12.5 h | 129 / 538 / 59 | – | | Mister Pizza | 03/04–17/06/2026 | 849 | 848 | 99.9% | 54 s | ~12.7 h | n/d | – | | “PersonalG” Campaign | 03/04–17/06/2026 | – | – | – | – | ~108 h | – | 35,825 |  ## Real Conversation Examples - Booking for **11 people** on Thursday at 8:00 PM: complete data collection and immediate confirmation. - Request “for 6 now”: Alice communicates an estimated **10-minute wait**. - **3 covers for lunch** with a celiac customer: verification and confirmation of the gluten-free menu. - **Group of 15**: complexity recognition and correct escalation to a human operator. ## Operational Impact - Continuous coverage: no calls left unanswered during critical periods. - Focus on service: front-of-house staff are not interrupted by the phone. - Actionable data: volumes, times, sentiment to optimize shifts and menus.  ## The Future of Automated Bookings in Restaurants The Dirigì Group case shows that voice AI for restaurants is already mature: measurable, scalable, and cost-effective. With growing demand and staff shortages, AI voice agents cover peak times without errors and maintain perceived quality. ## Conclusion DeepAgent's automated restaurant bookings reduce missed calls, confirm tables in under a minute, and free up your team. Want to see it in action? Request a demo: you will be called back from the number +39 068345191. ## Frequently Asked Questions ### How does an automated restaurant booking solution with Voice AI work? An AI voice assistant for restaurants answers the phone, collects date/time/covers and contact details, checks availability against a calendar or management system, and confirms in real-time. It can manage preferences (e.g., gluten-free), venue policies, and escalation to a human operator. It reduces average times, errors, and missed calls during peak hours. ### How does Voice AI reduce missed restaurant calls during peak times? It answers on the first ring, 24/7, routes calls between locations and available slots, and maintains intelligent queues. Scripts are optimized for quick decisions (confirmation, wait, alternatives) and escalation to human staff for complex cases. This way, the answer rate remains close to 100%, preserving covers and revenue even during peak periods. ### Can it be integrated with the venue's management system or CRM? Yes. The voice assistant integrates with reservation calendars, POS, or CRM systems via APIs. This allows for real-time availability checks, deduplication of contacts, operational notes (allergies, special occasions), and unified reporting. Integration makes automated restaurant bookings reliable and consistent with existing front and back-office processes. ### How does it handle special requests and large groups? The script includes dedicated intents for allergies, gluten-free options, joined tables, and special occasions. For groups above a certain threshold (e.g., 10–12 covers), the Voice AI suggests alternatives or transfers to an operator to finalize menus and deposits. This blend ensures courtesy, operational control, and flexibility, typical of a well-designed AI voice assistant for restaurants. ### Which KPIs should I monitor to evaluate a Voice AI project for restaurants? The main ones are: answer rate, success rate (confirmed bookings), average call duration, sentiment, missed calls, escalation percentage, confirmed covers, and automated conversation hours. Compare these KPIs pre/post implementation to estimate the impact on revenue and service. A 99%+ success rate and calls in ~60 seconds are excellent benchmarks.